code: def __init__(
      self,
      predictor: Callable,
      feature_names: List[str],
      categorical_names: Optional[Dict[int, List[str]]] = None,
      dtype: Type[np.generic] = np.float32,
      ohe: bool = False,
      seed: Optional[int] = None,
  ) -> None:
      super().__init__(
          predictor, feature_names, categorical_names, dtype, ohe, seed
      )
      if not ray.is_initialized():
          ray.init()
  
imports: import logging
  from typing import Any, Callable, Dict, List, Optional, Tuple, Type, Union
  import numpy
  import ray
  from alibi.api.interfaces import Explanation
  from alibi.utils.discretizer import Discretizer
  from alibi.utils.mapping import ohe_to_ord
  from .anchor_base import AnchorBaseBeam
  from .anchor_tabular import AnchorTabular, TabularSampler
  from alibi.utils.distributed import ActorPool
  from functools import partial
label_desc: Use image node_id 1 to create a new DistributedAnchorTabular object from inherited base classes: AnchorTabular with example: obj = DistributedAnchorTabular(predictor, feature_names, categorical_names, dtype, ohe, seed)